In 2023, we conducted a national survey to support our narrative change work. This document explores results from that survey related to poverty narratives, including their prevalence and differences across time and geography. It is intended as an internal resource for Narrative Change team members interested in better understanding the analyses we have conducted from this national survey. If you would like to quickly learn our main observations, search “Take-away” in this document or check out the deck we provided Wells Fargo (linked below).
For easy reference, below is a list of other resources or outputs relevant to this work:
Note: All analyses below are based on raw prevalence data. We have not engaged in any weighting or adjustments for demographic representation.
| question | narrative | Disagree / Strongly Disagree | Neither | Agree / Strongly Agree |
|---|---|---|---|---|
| Welfare makes people lazy. | welfare | 37% | 25% | 38% |
| There is a lot of fraud among welfare recipients. | welfare | 19% | 28% | 53% |
| An able-bodied person collecting welfare is ripping off the system. | welfare | 27% | 26% | 47% |
| Poor people think they deserve to be supported. | welfare | 34% | 34% | 32% |
| Many people take advantage of the welfare system. | welfare | 19% | 21% | 60% |
| Everyone has an equal opportunity to succeed. | meritocracy | 38% | 20% | 41% |
| We live in a meritocracy. Anyone can attain the American Dream. | meritocracy | 38% | 25% | 37% |
| Everyone has an equal opportunity to get a good education. | meritocracy | 44% | 19% | 37% |
| There will always be poor people. | fatalism | 8% | 22% | 70% |
| Almost by definition, someone has to be poor. | fatalism | 34% | 39% | 27% |
| Poverty is an inevitable outcome of society. | fatalism | 28% | 32% | 40% |
| Poor people need guidance to make better life choices. | paternalism | 20% | 34% | 46% |
| There would be less poverty if we helped the poor plan their lives better. | paternalism | 24% | 34% | 41% |
| Low income people could do better if someone helped them spend their money wisely. | paternalism | 29% | 38% | 33% |
| We should teach poor people how to manage their finances. | paternalism | 13% | 34% | 53% |
| Racism makes discrimination against poor minorities worse. | structural | 13% | 21% | 66% |
| Poor people experience prejudice and discrimination in hiring and promotion decisions at work. | structural | 16% | 28% | 57% |
| Poor people lack affordable housing options. | structural | 11% | 17% | 72% |
| Poor people lack affordable child care. | structural | 11% | 19% | 70% |
| Poor people lack opportunities for training & continuing education. | structural | 23% | 23% | 54% |
| narrative | mean | sd | se | n |
|---|---|---|---|---|
| welfare | 3.260019 | 0.9242634 | 0.0164185 | 3169 |
| meritocracy | 2.971284 | 1.0909388 | 0.0193794 | 3169 |
| fatalism | 3.264858 | 0.7650305 | 0.0135899 | 3169 |
| paternalism | 3.260177 | 0.7828676 | 0.0139068 | 3169 |
| structural | 3.667971 | 0.7722702 | 0.0137185 | 3169 |
Joint score of harmful narratives (i.e., all but structural): mean = 3.1890844, sd = 0.6378865, se = 0.0113314
According to https://greatdata.com/product/urban-vs-rural the
Department of Defense established the following designations for a ZIP
Code:
Urban: 3,000+ persons per square mile
Suburban: 1,000 ‐ 3,000 persons per square mile
Rural: less than 1,000 persons per square mile
This isn’t perfect because a lightly populated ZIP Code adjoining a
major metropolitan area would be mistakenly classified as a “Rural
Area”, but we’ll use it anyway.
Comparing these results with those observed in the 2021 national survey known as “pilot1c” (N = 461). Note that in the 2023 national survey, the options were: Strongly disagree, Disagree, Neither agree nor disagree, Agree, Strongly agree. On the other hand, in pilot1c, options were: Strongly agree, Somewhat agree, Neither agree nor disagree, Somewhat disagree, Strongly disagree (in that order). These have been reverse coded appropriately in the analyses below, but that can’t change the fact that the options presented were different.
In addition to the data discussed here, we collected data from an academic collaboration in 2022. In forthcoming analyses we will include that here, which will add a third time point that’s in between the two below.
T-tests to see if the 2023 average values of each narrative significantly differed from 2021:
| narrative | mean_2021 | mean_2023 | diff | perc_cng | t | p.value |
|---|---|---|---|---|---|---|
| welfare | 3.195662 | 3.260019 | 0.0643573 | 2% | 2.2515863 | 0.0244230 |
| meritocracy | 3.139552 | 2.971284 | -0.1682674 | -5% | -4.3557411 | 0.0000140 |
| fatalism | 3.167028 | 3.264858 | 0.0978293 | 3% | 2.7900253 | 0.0053291 |
| paternalism | 3.400217 | 3.260177 | -0.1400402 | -4% | -5.0926188 | 0.0000004 |
| structural | 3.711497 | 3.684443 | -0.0270537 | -1% | -0.8132479 | 0.4161885 |
All of the harmful narratives showed statistically significant differences from the 2021 pilot1c survey. The structural narrative did not. Endorsement of welfare fraud and fatalism increased, while meritocracy and paternalism decreased. The meritocracy and paternalism effect sizes were notably stronger. We would consider a 4-5% decrease to be a moderate-sized effect. No individual question stands out as driving these effects.
An extremely important caveat to the interpretation of this is that we do not know to what extent these differences reflect true changes over time vs. are the by-product of differential survey uptake. For example, it may be that more people from a certain group who tends to report lower meritocracy views (e.g. low-income non-white women) happened to make up a larger proportion of the 2023 survey than the 2021. The appropriate method to account for this would be to weight the results from various demographic groups to estimate what they would be if representation in both surveys were similar. Given the requirements of such an analysis and competing priorities, this is not something R&E plans to undertake at this time.
For more information about the demographics and representativeness of the 2023 national survey, see the descriptives analysis report. For a comparison to the demographics in the pilot1c 2021 survey, see the admin burden report.
r values:
| welfare | meritocracy | fatalism | paternalism | structural | |
|---|---|---|---|---|---|
| welfare | 1.0000000 | 0.5561695 | 0.3455670 | 0.3738031 | -0.3515070 |
| meritocracy | 0.5561695 | 1.0000000 | 0.1903214 | 0.2905976 | -0.4387403 |
| fatalism | 0.3455670 | 0.1903214 | 1.0000000 | 0.2525644 | 0.0489486 |
| paternalism | 0.3738031 | 0.2905976 | 0.2525644 | 1.0000000 | 0.1110818 |
| structural | -0.3515070 | -0.4387403 | 0.0489486 | 0.1110818 | 1.0000000 |
p-values (most are so low that they are difficult to represent computationally, like less than 0.00000000000000022):
| welfare | meritocracy | fatalism | paternalism | structural | |
|---|---|---|---|---|---|
| welfare | NA | 0 | 0.0000000 | 0 | 0.0000000 |
| meritocracy | 0 | NA | 0.0000000 | 0 | 0.0000000 |
| fatalism | 0 | 0 | NA | 0 | 0.0058501 |
| paternalism | 0 | 0 | 0.0000000 | NA | 0.0000000 |
| structural | 0 | 0 | 0.0058501 | 0 | NA |
All of these constructs technically have some level of correlation with one another, but the most notable is the relationship between welfare exploitation and meritocracy, which are correlated at r = 0.5561695, meaning that one variable explains 30.93% of the variance in the other. It is also notable that the structural narrative is negatively correlated with these two, but not with fatalism and paternalism.
Motivation: The concept and constructs that seek to quantitatively measure endorsement of narratives is relatively new. As we explore these constructs, it’s important to assess their validity. Ideologies like SDO, racial resentment, and right-wing authoritarianism are more established in the academic literature - their scales are more validated, and there is a lot of existing research on their importance as beliefs, who holds them, etc. We expect endorsements of harmful narratives to be related to beliefs in these ideologies. Showing that association helps us establish convergent validity. It furthermore gives us access to a full established literature to draw from for us (and others) to better understand our poverty narratives. These same goals are further supported by showing that these associations hold (and understanding to what extent) in this larger, newer survey we’ve conducted. The purpose of examining these worldviews is not to make the case that we should target them instead of narratives directly. Concepts like SDO, RWA, etc. are considered deeply held values. We do not have reason to expect that they would be any easier to change than poverty narratives themselves.
Approach: Below we run a series of nested models. First, examining just demographics, followed by the addition of the worldviews we’ve examined in the past (sdo, rwa, rrs), followed by the addition of worldviews we added in this survey (xenophobia & sexism). We can compare these models to assess the relative explanatory power that these worldviews have above and beyond demographics for predicting the joint (harmful) poverty narrative score. We can also look at the base demographics model to understand which demographics are more associated with harmful poverty narrative endorsement.
After removing certain responses (e.g. “Prefer not to say”, non-binary gender responses, etc.) in line with the decisions made in the Segmentation Analysis, we are left with a sample size of 2807 for this analysis.
lm(formula = joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology + education_grp + income_group + reli_imp2, data = worldviewmoddata)
| joint pov | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 3.50 | 3.42 – 3.57 | <0.001 |
| age_groupAge: 45-65 | -0.03 | -0.08 – 0.02 | 0.300 |
| age groupAge × above 65 | 0.01 | -0.04 – 0.07 | 0.651 |
|
race ethn [Black + Non-Hispanic] |
0.02 | -0.05 – 0.08 | 0.601 |
| race ethn [Hispanic] | 0.11 | 0.02 – 0.20 | 0.022 |
| race ethn [Other] | 0.13 | 0.05 – 0.21 | 0.001 |
| gender bin [Male] | 0.13 | 0.08 – 0.17 | <0.001 |
| polit ideology [Moderate] | -0.29 | -0.35 – -0.24 | <0.001 |
|
polit ideology [Somewhat or very liberal] |
-0.63 | -0.69 – -0.57 | <0.001 |
|
education grp [Associate / Some college] |
-0.08 | -0.14 – -0.02 | 0.009 |
| education grp [Bachelor] | -0.12 | -0.18 – -0.05 | 0.001 |
| education grp [Advanced] | -0.20 | -0.28 – -0.12 | <0.001 |
|
income group [$40,000 to $99,999] |
0.05 | 0.00 – 0.10 | 0.031 |
|
income group [$100,000 or more] |
0.15 | 0.09 – 0.22 | <0.001 |
| reli imp2 [Not important] | -0.13 | -0.17 – -0.08 | <0.001 |
| Observations | 2807 | ||
| R2 / R2 adjusted | 0.212 / 0.208 | ||
Demographics + sdo, rrs, rwa
lm(formula = joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology + education_grp + income_group + reli_imp2 + rwa + rrs + sdo, data = worldviewmoddata)
| joint pov | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 1.69 | 1.57 – 1.80 | <0.001 |
| age_groupAge: 45-65 | -0.05 | -0.09 – -0.00 | 0.031 |
| age groupAge × above 65 | -0.03 | -0.08 – 0.01 | 0.165 |
|
race ethn [Black + Non-Hispanic] |
0.18 | 0.13 – 0.24 | <0.001 |
| race ethn [Hispanic] | 0.12 | 0.05 – 0.20 | 0.001 |
| race ethn [Other] | 0.09 | 0.02 – 0.15 | 0.007 |
| gender bin [Male] | 0.04 | 0.00 – 0.08 | 0.027 |
| polit ideology [Moderate] | -0.03 | -0.07 – 0.02 | 0.250 |
|
polit ideology [Somewhat or very liberal] |
-0.07 | -0.13 – -0.02 | 0.008 |
|
education grp [Associate / Some college] |
-0.02 | -0.07 – 0.02 | 0.302 |
| education grp [Bachelor] | -0.03 | -0.08 – 0.03 | 0.330 |
| education grp [Advanced] | -0.06 | -0.12 – 0.00 | 0.056 |
|
income group [$40,000 to $99,999] |
0.07 | 0.03 – 0.11 | <0.001 |
|
income group [$100,000 or more] |
0.17 | 0.12 – 0.22 | <0.001 |
| reli imp2 [Not important] | -0.02 | -0.06 – 0.02 | 0.258 |
| rwa | 0.19 | 0.17 – 0.21 | <0.001 |
| rrs | 0.23 | 0.21 – 0.26 | <0.001 |
| sdo | 0.10 | 0.07 – 0.13 | <0.001 |
| Observations | 2807 | ||
| R2 / R2 adjusted | 0.495 / 0.492 | ||
Worldview model + sexism, xenophobia
lm(formula = joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology + education_grp + income_group + reli_imp2 + rwa + rrs + sdo + sexism + xenophobia, data = worldviewmoddata)
| joint pov | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 1.52 | 1.41 – 1.64 | <0.001 |
| age_groupAge: 45-65 | -0.06 | -0.10 – -0.01 | 0.008 |
| age groupAge × above 65 | -0.04 | -0.09 – 0.00 | 0.071 |
|
race ethn [Black + Non-Hispanic] |
0.17 | 0.11 – 0.22 | <0.001 |
| race ethn [Hispanic] | 0.13 | 0.06 – 0.20 | <0.001 |
| race ethn [Other] | 0.09 | 0.03 – 0.15 | 0.005 |
| gender bin [Male] | 0.04 | 0.00 – 0.08 | 0.031 |
| polit ideology [Moderate] | 0.01 | -0.03 – 0.06 | 0.508 |
|
polit ideology [Somewhat or very liberal] |
0.00 | -0.06 – 0.06 | 0.987 |
|
education grp [Associate / Some college] |
-0.03 | -0.07 – 0.02 | 0.283 |
| education grp [Bachelor] | -0.02 | -0.07 – 0.04 | 0.546 |
| education grp [Advanced] | -0.04 | -0.10 – 0.02 | 0.179 |
|
income group [$40,000 to $99,999] |
0.07 | 0.03 – 0.11 | 0.001 |
|
income group [$100,000 or more] |
0.17 | 0.12 – 0.22 | <0.001 |
| reli imp2 [Not important] | -0.01 | -0.05 – 0.03 | 0.598 |
| rwa | 0.15 | 0.13 – 0.17 | <0.001 |
| rrs | 0.19 | 0.16 – 0.21 | <0.001 |
| sdo | 0.08 | 0.05 – 0.11 | <0.001 |
| sexism | 0.02 | -0.00 – 0.05 | 0.079 |
| xenophobia | 0.11 | 0.08 – 0.13 | <0.001 |
| Observations | 2807 | ||
| R2 / R2 adjusted | 0.513 / 0.510 | ||
Analysis of Variance Table
Model 1: joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology +
education_grp + income_group + reli_imp2
Model 2: joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology +
education_grp + income_group + reli_imp2 + rwa + rrs + sdo
Model 3: joint_pov ~ age_group + race_ethn + gender_bin + polit_ideology +
education_grp + income_group + reli_imp2 + rwa + rrs + sdo +
sexism + xenophobia
Res.Df RSS Df Sum of Sq F Pr(>F)
1 2792 930.04
2 2789 595.55 3 334.49 540.659 < 0.00000000000000022 ***
3 2787 574.74 2 20.81 50.458 < 0.00000000000000022 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
| Dependent variable: | |||
| joint_pov | |||
| (1) | (2) | (3) | |
| age_groupAge: 45-65 | -0.027 | -0.046** | -0.055*** |
| (0.026) | (0.021) | (0.021) | |
| age_groupAge: above 65 | 0.013 | -0.033 | -0.042* |
| (0.029) | (0.024) | (0.023) | |
| race_ethnBlack + Non-Hispanic | 0.018 | 0.182*** | 0.168*** |
| (0.034) | (0.028) | (0.027) | |
| race_ethnHispanic | 0.107** | 0.124*** | 0.132*** |
| (0.047) | (0.037) | (0.037) | |
| race_ethnOther | 0.128*** | 0.085*** | 0.087*** |
| (0.039) | (0.031) | (0.031) | |
| gender_binMale | 0.129*** | 0.041** | 0.040** |
| (0.023) | (0.018) | (0.018) | |
| polit_ideologyModerate | -0.294*** | -0.026 | 0.015 |
| (0.027) | (0.023) | (0.023) | |
| polit_ideologySomewhat or very liberal | -0.629*** | -0.074*** | 0.0005 |
| (0.031) | (0.028) | (0.029) | |
| education_grpAssociate / Some college | -0.078*** | -0.025 | -0.025 |
| (0.030) | (0.024) | (0.024) | |
| education_grpBachelor | -0.116*** | -0.026 | -0.016 |
| (0.034) | (0.027) | (0.027) | |
| education_grpAdvanced | -0.201*** | -0.061* | -0.043 |
| (0.040) | (0.032) | (0.032) | |
| 99,999 | 0.055** | 0.074*** | 0.069*** |
| (0.025) | (0.020) | (0.020) | |
| 100,000 or more | 0.152*** | 0.170*** | 0.167*** |
| (0.033) | (0.027) | (0.026) | |
| reli_imp2Not important | -0.125*** | -0.023 | -0.010 |
| (0.025) | (0.020) | (0.020) | |
| rwa | 0.188*** | 0.153*** | |
| (0.010) | (0.011) | ||
| rrs | 0.232*** | 0.189*** | |
| (0.012) | (0.013) | ||
| sdo | 0.100*** | 0.079*** | |
| (0.015) | (0.015) | ||
| sexism | 0.024* | ||
| (0.013) | |||
| xenophobia | 0.106*** | ||
| (0.011) | |||
| Constant | 3.495*** | 1.687*** | 1.521*** |
| (0.037) | (0.057) | (0.059) | |
| Observations | 2,807 | 2,807 | 2,807 |
| R2 | 0.212 | 0.495 | 0.513 |
| Adjusted R2 | 0.208 | 0.492 | 0.510 |
| Residual Std. Error | 0.577 (df = 2792) | 0.462 (df = 2789) | 0.454 (df = 2787) |
| F Statistic | 53.594*** (df = 14; 2792) | 160.994*** (df = 17; 2789) | 154.467*** (df = 19; 2787) |
| Note: | p<0.1; p<0.05; p<0.01 | ||
The analyses below are in response to ad hoc requests from the city design teams. They were run for a particular design/city, but are included below as they may nonetheless be of interest to others.
Some of our design work and goals are focused on voting and there is interest to understand generational differences in narrative endorsement.
What is the representation of different age groups in our sample?
| age_group | respondents | proportion |
|---|---|---|
| 18-28 | 330 | 0.1041338 |
| 29-44 | 771 | 0.2432944 |
| 45-64 | 1149 | 0.3625749 |
| 65+ | 919 | 0.2899968 |
| narrative | 18-28 | 29-44 | 45-64 | 65+ |
|---|---|---|---|---|
| welfare | 3.130909 | 3.170947 | 3.266667 | 3.372797 |
| meritocracy | 2.676768 | 2.834414 | 3.029011 | 3.119695 |
| fatalism | 3.381818 | 3.364462 | 3.245431 | 3.163584 |
| paternalism | 3.339394 | 3.273671 | 3.192559 | 3.304951 |
| structural | 3.809091 | 3.759533 | 3.632724 | 3.584548 |
DC is interested in these questions more particularly.
| question | 18-28 | 29-44 | 45-64 | 65+ |
|---|---|---|---|---|
| Low income people could do better if someone helped them spend their money wisely. | 3.172727 | 3.035020 | 2.939948 | 3.090316 |
| Poor people need guidance to make better life choices. | 3.318182 | 3.251621 | 3.252393 | 3.428727 |
| There would be less poverty if we helped the poor plan their lives better. | 3.321212 | 3.264591 | 3.142733 | 3.226333 |
| We should teach poor people how to manage their finances. | 3.545454 | 3.543450 | 3.435161 | 3.474429 |
Continuous data, instead of bins:
DC is interested in these questions more particularly.
| question | 18-28 | 29-44 | 45-64 | 65+ |
|---|---|---|---|---|
| COVID assistance, like stimulus checks | 3.718182 | 3.909209 | 3.532637 | 3.335147 |
| Child tax credit - a tax credit given to families with dependent children | 3.763636 | 4.059663 | 3.969539 | 3.884657 |
| Guaranteed income program - provides a periodic unrestricted cash stipend to people’s income | 3.421212 | 3.608301 | 3.220191 | 2.856366 |
| Housing assistance, like temporary shelters and long-term affordable housing | 3.927273 | 4.107652 | 3.987815 | 3.896627 |
| Medicaid - covers healthcare costs for people with low incomes | 3.990909 | 4.160830 | 4.077459 | 4.025027 |
| Supplemental Nutrition Assistance Program (SNAP) - food-assistance to people with low incomes, also known as “Food Stamps” | 4.042424 | 4.079118 | 4.057441 | 4.006529 |
| TANF - provide temporary financial assistance for people with dependent children | 3.815151 | 3.939040 | 3.817232 | 3.697497 |
DC is interested in these questions more particularly.
| question | 18-28 | 29-44 | 45-64 | 65+ |
|---|---|---|---|---|
| Complex, detailed rules are often necessary to ensure that people are treated equally. | 3.290909 | 3.395590 | 3.161010 | 3.133841 |
| Food stamp programs should restrict the kind of food that you can buy. | 2.621212 | 2.941634 | 3.023499 | 3.362350 |
| If people want to access public services and benefits, it is only fair that they have to make a significant effort to get them. | 3.075758 | 3.286641 | 3.355962 | 3.500544 |
| It is acceptable that people face some hassles when they are in contact with the government. | 2.878788 | 2.782101 | 2.579635 | 2.628944 |
| It is acceptable that people sometimes feel that it is difficult and time-consuming to apply for government services and benefits. | 3.212121 | 3.201038 | 3.104439 | 3.067465 |
| People receiving unemployment benefits should prove they are actively looking for jobs. | 3.624242 | 3.752270 | 3.912097 | 4.103373 |
| People should be responsible for figuring out how to access government services themselves; it is not the government’s responsibility to help them. | 2.578788 | 2.660182 | 2.530896 | 2.486398 |
| Social assistance programs should have work requirements. | 3.290909 | 3.457847 | 3.542211 | 3.737758 |
| Social assistance programs should require financial counseling. | 3.484849 | 3.623865 | 3.575283 | 3.700762 |
| Stress and uncertainty are inevitable when people apply for government services and benefits. | 3.487879 | 3.536965 | 3.496084 | 3.466812 |
DC is interested in these questions more particularly. Note: The statements on the 1-5 scale are different for these questions than most others. Be sure to reference the actual survey for their meaning.
| question | 18-28 | 29-44 | 45-64 | 65+ |
|---|---|---|---|---|
| A guaranteed income program for my community would be… | 3.766667 | 3.817121 | 3.425587 | 3.101197 |
| A guaranteed income program for my life would be… | 3.975758 | 3.964980 | 3.623151 | 3.226333 |
| In general, do you support guaranteed income programs? | 3.818182 | 3.726329 | 3.316797 | 2.840044 |
Ad hoc analyses to inform audience for NYC game development
We have 1331 responses from people under 50 years old (which is 42% of the full sample). Looking just among that age group:
| question | narrative | Disagree / Strongly Disagree | Neither | Agree / Strongly Agree |
|---|---|---|---|---|
| Welfare makes people lazy. | welfare | 42% | 25% | 34% |
| There is a lot of fraud among welfare recipients. | welfare | 22% | 29% | 49% |
| An able-bodied person collecting welfare is ripping off the system. | welfare | 33% | 29% | 38% |
| Poor people think they deserve to be supported. | welfare | 33% | 34% | 33% |
| Many people take advantage of the welfare system. | welfare | 23% | 23% | 54% |
| Everyone has an equal opportunity to succeed. | meritocracy | 44% | 19% | 37% |
| We live in a meritocracy. Anyone can attain the American Dream. | meritocracy | 45% | 23% | 31% |
| Everyone has an equal opportunity to get a good education. | meritocracy | 48% | 20% | 32% |
| There will always be poor people. | fatalism | 9% | 19% | 71% |
| Almost by definition, someone has to be poor. | fatalism | 33% | 37% | 30% |
| Poverty is an inevitable outcome of society. | fatalism | 24% | 30% | 47% |
| Poor people need guidance to make better life choices. | paternalism | 24% | 31% | 45% |
| There would be less poverty if we helped the poor plan their lives better. | paternalism | 25% | 30% | 45% |
| Low income people could do better if someone helped them spend their money wisely. | paternalism | 31% | 34% | 35% |
| We should teach poor people how to manage their finances. | paternalism | 14% | 31% | 55% |
| Racism makes discrimination against poor minorities worse. | structural | 11% | 20% | 69% |
| Poor people experience prejudice and discrimination in hiring and promotion decisions at work. | structural | 14% | 24% | 61% |
| Poor people lack affordable housing options. | structural | 11% | 17% | 72% |
| Poor people lack affordable child care. | structural | 11% | 19% | 70% |
| Poor people lack opportunities for training & continuing education. | structural | 18% | 22% | 60% |
Meritocracy endorsement is lower in this group than in older participants.
Social factors
One framework we chose is social change theory, which includes the varialbles:
We chose to measure only social identity and social connectedness. This framework represents our relationship with the social ecosystem and how that might explain differences in narrative endorsement.
Basic stats
Correlations
r values:
Colored according to the following rules of thumb:
p-values:
Observations